An innovative approach based on machine learning to evaluate the risk factors importance in diagnosing keratoconus

•This research gives strong insight into the significance of keratoconus risk factors in the predictive modelling process.•The developed ML model can provide better performance in diagnosis compared to other models in the literature.•We show a significant increase in correlation and accuracy with the inclusion of risk factor data in the training process.•The results can improve the diagnosis process in clinical settings and provide insight into the risk factors’ importance.•This study demonstrates the significance of machine learning techniques and risk factor data for keratoconus diagnosis.